Suppr超能文献

对接受血液透析治疗的患者进行非接触生命体征监测。

Non-contact vital-sign monitoring of patients undergoing haemodialysis treatment.

机构信息

Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK.

Oxford Kidney Unit, Oxford University Hospitals National Health Service Trust, Oxford, UK.

出版信息

Sci Rep. 2020 Oct 28;10(1):18529. doi: 10.1038/s41598-020-75152-z.

Abstract

A clinical study was designed to record a wide range of physiological values from patients undergoing haemodialysis treatment in the Renal Unit of the Churchill Hospital in Oxford. Video was recorded for a total of 84 dialysis sessions from 40 patients during the course of 1 year, comprising an overall video recording time of approximately 304.1 h. Reference values were provided by two devices in regular clinical use. The mean absolute error between the heart rate estimates from the camera and the average from two reference pulse oximeters (positioned at the finger and earlobe) was 2.8 beats/min for over 65% of the time the patient was stable. The mean absolute error between the respiratory rate estimates from the camera and the reference values (computed from the Electrocardiogram and a thoracic expansion sensor-chest belt) was 2.1 breaths/min for over 69% of the time for which the reference signals were valid. To increase the robustness of the algorithms, novel methods were devised for cancelling out aliased frequency components caused by the artificial light sources in the hospital, using auto-regressive modelling and pole cancellation. Maps of the spatial distribution of heart rate and respiratory rate information were developed from the coefficients of the auto-regressive models. Most of the periods for which the camera could not produce a reliable heart rate estimate lasted under 3 min, thus opening the possibility to monitor heart rate continuously in a clinical environment.

摘要

一项临床研究旨在记录牛津丘吉尔医院肾脏科接受血液透析治疗的患者的广泛生理值。在 1 年的时间里,从 40 名患者中总共记录了 84 次透析过程的视频,总视频录制时间约为 304.1 小时。参考值由两种常规临床使用的设备提供。在患者稳定的大部分时间(超过 65%)内,摄像机估计的心率与两个参考脉搏血氧仪(置于手指和耳垂处)的平均值之间的平均绝对误差为 2.8 次/分钟。在参考信号有效的大部分时间内(超过 69%),摄像机估计的呼吸率与参考值(通过心电图和胸部扩展传感器-胸带计算得出)之间的平均绝对误差为 2.1 次/分钟。为了提高算法的鲁棒性,设计了新的方法来消除医院人工光源引起的混叠频率分量,使用自回归建模和极点消除。心率和呼吸率信息的空间分布图是从自回归模型的系数中开发出来的。摄像机无法产生可靠心率估计的大部分时间段持续不到 3 分钟,因此有可能在临床环境中连续监测心率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7532/7595175/f00256072ad9/41598_2020_75152_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验